Solitary

1 Solitary

# Load necessary libraries

# Reading and wrangling
library(googlesheets4)
library(readr)
library(tidyverse)
library(janitor)
library(lubridate)
library(DT)

# Plotting
library(ggplot2)
library(RColorBrewer)

# Tables
library(kableExtra)

# Load custom function
source("function_clean_facility_names.R", local = knitr::knit_global())

# Read in Sheet G-324A-19
df_324 <- read_sheet("https://docs.google.com/spreadsheets/d/1im5VSi3bIEi13O8WQ56wEIXSyNEstbGMylXXgD9bAG0/edit#gid=1858227071",
                 sheet="G-324A-19",
                 col_names = TRUE,
                 col_types = "c") %>% 
  clean_names() %>% 
  
  # Run custom cleaning function
  clean_facility_names() %>% 
  
  # df specific changes
  mutate(facility = as.factor(facility),
         state = as.factor(state),
         date = mdy(inspection_date),
         current_inspection_date_from = mdy(current_inspection_date_from),
         current_inspection_date_to = mdy(current_inspection_date_to)
         ) %>% 
  relocate(date, .before = inspection_date) %>% 
  mutate_at(c(20:49), as.numeric)

## Reading from "000inspection_forms"

## Range "'G-324A-19'"

## Warning: Expected 2 pieces. Missing pieces filled with `NA` in 1 rows [182].

## Warning: 1 failed to parse.

## Warning in mask$eval_all_mutate(quo): NAs introduced by coercion

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# Read Google Sheet incident worksheet, convert to data frame, and wrangle
df_324_inc <- read_sheet("https://docs.google.com/spreadsheets/d/1im5VSi3bIEi13O8WQ56wEIXSyNEstbGMylXXgD9bAG0/edit#gid=1858227071",
                 sheet="G-324A-19-inc",
                 col_types = "c") %>% 
  clean_names() %>%
  
  # Run custom cleaning function
  clean_facility_names() %>% 


  # df_specific changes
  unite(date, year:month) %>% 
  mutate(facility = as.factor(facility),
         state = as.factor(state),
         date = ym(date)
         ) %>% 
  mutate_at(c(6:76), as.numeric)

## Reading from "000inspection_forms"

## Range "'G-324A-19-inc'"

## New names:
## * `Sexual abuse allegations detainee on staff/contractor/volunteer` -> `Sexual abuse allegations detainee on staff/contractor/volunteer...29`
## * `Sexual abuse allegations detainee on staff/contractor/volunteer` -> `Sexual abuse allegations detainee on staff/contractor/volunteer...34`

## Warning: Expected 2 pieces. Missing pieces filled with `NA` in 12 rows [2144, 2145, 2146, 2147, 2148, 2149, 2150, 2151, 2152,
## 2153, 2154, 2155].

## Warning: 1 failed to parse.

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1.1 Summary Tables

Of the present 163 inspections reviewed so far, there are more than 34,000 instances of solitary. That is roughly 208 instances of solitary per inspection.

df_solitary <- df_324_inc %>%
  
  # Select a subset of columns to work with
  select(id,
         facility,
         date,
         detainees_placed_in_administrative_segregation:
           detainees_placed_in_segregation_for_mental_health_reasons) %>% 
  
  # Need the rowwise function to compute a row-at-a-time
  # in the following mutate function
  rowwise(id) %>% 
  
  # Create new total column
  mutate(total_segregation = sum(c_across(detainees_placed_in_administrative_segregation:
                 detainees_placed_in_segregation_for_mental_health_reasons))) %>% 
  
  # Tidy
  pivot_longer(.,
               cols= detainees_placed_in_administrative_segregation:
                 total_segregation,
               names_to = "segregation_type",
               values_to = "segregation_count") %>% 
  
  # Remove NA
  drop_na() %>% 
  
  # Explicitly set factor levels
  mutate(segregation_type = factor(segregation_type, levels = c(
    "detainees_placed_in_administrative_segregation",
    "detainees_placed_in_disciplinary_segregation",
    "detainees_placed_in_segregation_for_medical_reasons",
    "detainees_placed_in_segregation_for_mental_health_reasons",
    "total_segregation"
  )))

df_solitary %>% 
  group_by(segregation_type) %>% 
  summarise(`Total Solitary by Type` = sum(segregation_count)) %>% 
  ungroup() %>% 
  kable(caption = "Total Solitary by Type",
        col.names = c("Solitary Type", "Total Solitary Type")) %>% 
  kable_styling(c("hover", "striped", "condensed", "responsive"))

Table 1.1: Total Solitary by Type

Solitary Type	Total Solitary Type
detainees_placed_in_administrative_segregation	17236
detainees_placed_in_disciplinary_segregation	9551
detainees_placed_in_segregation_for_medical_reasons	9869
detainees_placed_in_segregation_for_mental_health_reasons	1003
total_segregation	37336

df_solitary %>% 
  group_by(facility) %>% 
  summarise(total_segregation = sum(segregation_count)) %>% 
  arrange(desc(total_segregation)) %>% 
  ungroup() %>% 
  kable(caption = "Total Solitary by Facility",
        col.names = c("Facility", "Total Solitary by Facility")) %>% 
  kable_styling(c("hover", "striped", "condensed", "responsive")) %>% 
  scroll_box(height = "300px")

Table 1.1: Total Solitary by Facility

Facility	Total Solitary by Facility
Krome Service Processing Center	10882
Eloy Detention Center	4556
El Paso Service Processing Center	3310
Prairieland Detention Center	2788
Henderson Detention Center	2638
Krome North Service Processing Center	2510
Winn Correctional Center	2474
Caroline Detention Facility	2438
Otero County Processing Center	2332
La Palma Correctional Center	2198
Adelanto ICE Processing Center - West	2178
Irwin County Detention Center	2172
River Correctional Center	1898
Stewart Detention Center	1814
South Texas ICE Processing Center	1696
Adams County Correctional Center	1456
York County Prison	1418
Montgomery Processing Center	1324
Adelanto ICE Processing Center - East	1308
Otay Mesa Detention Center	1266
Jackson Parish Correctional Center	1248
Aurora ICE Processing Center	1138
Aurora ICE Processing Center II - Annex	1138
Northwest ICE Processing Center	1028
Immigration Centers of America - Farmville	1006
Imperial Regional Detention Facility	1006
Glades County Detention Center	974
Port Isabel Service Processing Center	932
LaSalle ICE Processing Center	928
Sherburne County Jail	796
Pulaski County Detention Center	688
Catahoula Correctional Center	662
Pike County Correctional Facility	606
Jena LaSalle Detention Facility	602
Pine Prairie ICE Processing Center	554
Baker County Detention Center	468
McHenry County Adult Correctional Facility	462
Bluebonnet Detention Center	452
Florence Service Processing Center	388
Bergen County Jail	372
Houston Contract Detention Facility	372
Bristol County Jail and House of Correction	360
Wakulla County Detention Facility	342
Polk County Adult Detention Center	296
Calhoun County Correctional Center	274
Freeborn County Adult Detention Center	256
Richwood Correctional Center	256
Yuba County Jail	224
Hudson County Corrections and Rehabilitation Center	220
Essex County Correctional Facility	213
Limestone County Detention Center	206
Clinton County Correctional Facility	196
Donald W. Wyatt Detention Facility	194
Plymouth County Correctional Facility	176
El Valle Detention Facility	172
Dodge County Detention Facility	162
Geauga County Jail	150
Allen Parish Public Safety Complex	142
LaSalle Correctional Center	140
Okmulgee County Jail - Moore Detention Facility	140
Johnson County Corrections Center	136
Saint Clair County Jail	134
Elizabeth Contract Detention Facility	132
Folkston ICE Processing Center	126
Jerome Combs Detention Center	124
Joe Corley Processing Center	120
Nye County Detention Center	120
Mesa Verde ICE Processing Facility	108
Seneca County Jail	102
Kay County Detention Center	92
Worcester County Jail	82
Eden Detention Center	78
Clay County Jail	76
Butler County Jail	72
Torrance County Detention Facility	58
Hardin County Jail	56
Bossier Parish Corrections Center	54
Webb County Detention Center	54
Chippewa County Correctional Facility	50
David L. Moss Criminal Justice Center	46
Cambria County Prison	44
Montgomery County Jail	42
Strafford County Department of Corrections	42
Washoe County Detention Center	42
Hall County Department of Corrections	40
Rio Grande Detention Center	36
CCA Florence Correctional Center	34
Cibola County Correctional Center	32
Boone County Jail	28
Golden State Annex	26
Folkston ICE Processing Center Annex	24
Desert View Annex	22
Laredo Processing Center	22
Cass County Jail	20
Morgan County Adult Detention Center	20
Alamance County Detention Center	16
Teller County Jail	16
Northern Oregon Correctional Facility	14
Sheriff Al Cannon Detention Center	14
Carver County Jail	10
Howard County Detention Center	10
Orange County Correctional Facility	8
Shawnee County Department of Corrections - Adult Detention Center	6
Christian County Jail	4
Rolling Plains Detention Center	4
San Luis Regional Detention Center	4
Brooks County Detention Center	0
Broward Transitional Center	0
Coastal Bend Detention Center	0
Dorchester County Detention Center	0
Douglas County Department of Corrections	0
East Hidalgo Detention Center	0
LaSalle County Regional Detention Center	0
Monroe County Inmate Dormitory	0
Morrow County Correctional Facility	0
Platte County Detention Center	0
Robert A. Deyton Detention Facility	0
South Louisiana ICE Processing Center	0
T. Don Hutto Residential Center	0
Val Verde Correctional Facility	0
West Texas Detention Facility	0
Western Tennessee Detention Facility	0
Willacy County Regional Detention Facility	0

1.2 Facet Plots of Solitary by Facility

# Generating a linetype vector for use in the plot
plot_lines <- c(
    "solid",
    "solid",
    "solid",
    "solid",
    "dotted"
    )

# Use Color Brewer to set colors and modify
# the last color to be black for totals.
plot_colors <- brewer.pal(5, "Paired")
plot_colors[5] <- "#000000"

# Create plot labels
plot_labels <- c(
    "Administrative",
    "Disciplinary",
    "Medical",
    "Mental Health",
    "Total")

df_solitary %>% 

# Calling the plot and formatting
  ggplot(aes(x=date,
             y = segregation_count,
             linetype = segregation_type))+
  geom_line(aes(color = segregation_type), size = .65) +
  
  # Set the color
  scale_color_manual(
  values = plot_colors,
  name = "Solitary Type:",
  labels = plot_labels)+
  
  # Set the linetype
  scale_linetype_manual(
    values = plot_lines,
      name = "Solitary Type:",
    labels = plot_labels)+
  
  
  labs(title = "Reported Use of Solitary")+
  ylab("Number of Individuals Palced in Solitary")+
  xlab("Date")+
  theme(
    strip.text = element_text(size = 8),
    legend.position = "bottom"
    )+
    facet_wrap(~ facility, ncol=3)

1.3 Solitary Over 60 Days

# Use Color Brewer to set colors and modify
# the last color to be black for totals.
plot_colors <- brewer.pal(5, "Paired")
plot_colors[5] <- "#000000"

# Call the dataframe and select cols
df_324 %>% 
  select(id,
         facility,
         state,
         date,
         fac_operator,
         admin_seg_60_ice,
         disc_seg_60_ice) %>% 
  drop_na() %>% 
  
  # Need the rowwise function to compute a row-at-a-time
  # in the following mutate function
  rowwise(id) %>% 
  
  # Generate total col
  mutate(total_seg_60 = sum(c_across(
       admin_seg_60_ice:
       disc_seg_60_ice
  ))) %>%
  
  # Make tidy and filter
  pivot_longer(cols = admin_seg_60_ice:disc_seg_60_ice,
               names_to = "segregation_60_type",
               values_to = "segregation_60_count") %>%
  filter(segregation_60_type %in% c("admin_seg_60_ice", "disc_seg_60_ice")&
           segregation_60_count > 0) %>%
  
  # Initiate the plot and sort by sum
  ggplot(aes(x = segregation_60_count,
             y=reorder(fac_operator, segregation_60_count, sum),
             fill=segregation_60_type))+
  geom_bar(stat = "identity")+
  
  # Set the color fill
  scale_fill_brewer(type = "qual",
                    palette = "Paired",
                    name = "Segregation > 60 Type",
                    labels = c("Administrative",
                               "Disciplinary"))+
  labs(title= "Segregation > 60 Days by Facility Operator",
        x = "Segregation > 60 Days Count",
        y = "Facility Operator")+
  theme(legend.position = "bottom")